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- All Subjects: Neurosciences
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Description
The brain is a fundamental target of the stress response that promotes adaptation and survival but the repeated activation of the stress response has the potential alter cognition, emotion, and motivation, key functions of the limbic system. Three structures of the limbic system in particular, the hippocampus, medial prefrontal cortex (mPFC), and amygdala, are of special interest due to documented structural changes and their implication in post-traumatic stress disorder (PTSD). One of many notable chronic stress-induced changes include dendritic arbor restructuring, which reflect plasticity patterns in parallel with the direction of alterations observed in functional imaging studies in PTSD patients. For instance, chronic stress produces dendritic retraction in the hippocampus and mPFC, but dendritic hypertrophy in the amygdala, consistent with functional imaging in patients with PTSD. Some have hypothesized that these limbic region's modifications contribute to one's susceptibility to develop PTSD following a traumatic event. Consequently, we used a familiar chronic stress procedure in a rat model to create a vulnerable brain that might develop traits consistent with PTSD when presented with a challenge. In adult male rats, chronic stress by wire mesh restraint (6h/d/21d) was followed by a variety of behavioral tasks including radial arm water maze (RAWM), fear conditioning and extinction, and fear memory reconsolidation to determine chronic stress effects on behaviors mediated by these limbic structures. In chapter 2, we corroborated past findings that chronic stress caused hippocampal CA3 dendritic retraction. Importantly, we present new findings that CA3 dendritic retraction corresponded with poor spatial memory in the RAWM and that these outcomes reversed after a recovery period. In chapter 3, we also showed that chronic stress impaired mPFC-mediated extinction memory, findings that others have reported. Using carefully assessed behavior, we present new findings that chronic stress impacted nonassociative fear by enhancing contextual fear during extinction that generalized to a new context. Moreover, the generalization behavior corresponded with enhanced functional activation in the hippocampus and amygdala during fear extinction memory retrieval. In chapter 5, we showed for the first time that chronic stress enhanced amygdala functional activation during fear memory retrieval, i.e., reactivation. Moreover, these enhanced fear memories were resistant to protein synthesis interference to disrupt a previously formed memory, called reconsolidation in a novel attempt to weaken chronic stress enhanced traumatic memory. Collectively, these studies demonstrated the plastic and dynamic effects of chronic stress on limbic neurocircuitry implicated in PTSD. We showed that chronic stress created a structural and functional imbalance across the hippocampus, mPFC, and amygdala, which lead to a PTSD-like phenotype with persistent and exaggerated fear following fear conditioning. These behavioral disruptions in conjunction with morphological and functional imaging data reflect a chronic stress-induced imbalance between hippocampal and mPFC regulation in favor of amygdala function overdrive, and supports a novel approach for traumatic memory processing in PTSD.
ContributorsHoffman, Ann (Author) / Conrad, Cheryl D. (Thesis advisor) / Olive, M. Foster (Committee member) / Hammer, Jr., Ronald P. (Committee member) / Sanabria, Federico (Committee member) / Arizona State University (Publisher)
Created2013
Description
Chronic restraint stress impairs hippocampal-mediated spatial learning and memory, which improves following a post-stress recovery period. Here, we investigated whether brain derived neurotrophic factor (BDNF), a protein important for hippocampal function, would alter the recovery from chronic stress-induced spatial memory deficits. Adult male Sprague-Dawley rats were infused into the hippocampus with adeno- associated viral vectors containing the coding sequence for short interfering (si)RNA directed against BDNF or a scrambled sequence (Scr), with both containing the coding information for green fluorescent protein to aid in anatomical localization. Rats were then chronically restrained (wire mesh, 6h/d/21d) and assessed for spatial learning and memory using a radial arm water maze (RAWM) either immediately after stressor cessation (Str-Imm) or following a 21-day post-stress recovery period (Str-Rec). All groups learned the RAWM task similarly, but differed on the memory retention trial. Rats in the Str-Imm group, regardless of viral vector contents, committed more errors in the spatial reference memory domain than did non-stressed controls. Importantly, the typical improvement in spatial memory following recovery from chronic stress was blocked with the siRNA against BDNF, as Str-Rec-siRNA performed worse on the RAWM compared to the non-stressed controls or Str-Rec-Scr. These effects were specific for the reference memory domain as repeated entry errors that reflect spatial working memory were unaffected by stress condition or viral vector contents. These results demonstrate that hippocampal BDNF is necessary for the recovery from stress-induced hippocampal dependent spatial memory deficits in the reference memory domain.
ContributorsOrtiz, J. Bryce (Author) / Conrad, Cheryl D. (Thesis advisor) / Olive, M. Foster (Committee member) / Taylor, Sara (Committee member) / Bimonte-Nelson, Heather A. (Committee member) / Arizona State University (Publisher)
Created2013
Description
During attempted fixation, the eyes are not still but continue to produce so called "fixational eye movements", which include microsaccades, drift, and tremor. Microsaccades are thought to help prevent and restore vision loss during fixation, and to correct fixation errors, but how they contribute to these functions remains a matter of debate. This dissertation presents the results of four experiments conducted to address current controversies concerning the role of microsaccades in visibility and oculomotor control.
The first two experiments set out to correlate microsaccade production with the visibility of foveal and peripheral targets of varied spatial frequencies, during attempted fixation. The results indicate that microsaccades restore the visibility of both peripheral targets and targets presented entirely within the fovea, as a function of their spatial frequency characteristics.
The last two experiments set out to determine the role of microsaccades and drifts on the correction of gaze-position errors due to blinks in human and non-human primates, and to characterize microsaccades forming square-wave jerks (SWJs) in non-human primates. The results showed that microsaccades, but not drifts, correct gaze-position errors due to blinks, and that SWJ production and dynamic properties are equivalent in human and non-human primates.
These combined findings suggest that microsaccades, like saccades, serve multiple and non-exclusive functional roles in vision and oculomotor control, as opposed to having a single specialized function.
The first two experiments set out to correlate microsaccade production with the visibility of foveal and peripheral targets of varied spatial frequencies, during attempted fixation. The results indicate that microsaccades restore the visibility of both peripheral targets and targets presented entirely within the fovea, as a function of their spatial frequency characteristics.
The last two experiments set out to determine the role of microsaccades and drifts on the correction of gaze-position errors due to blinks in human and non-human primates, and to characterize microsaccades forming square-wave jerks (SWJs) in non-human primates. The results showed that microsaccades, but not drifts, correct gaze-position errors due to blinks, and that SWJ production and dynamic properties are equivalent in human and non-human primates.
These combined findings suggest that microsaccades, like saccades, serve multiple and non-exclusive functional roles in vision and oculomotor control, as opposed to having a single specialized function.
ContributorsCostela, Francisco M (Author) / Crook, Sharon M (Committee member) / Martinez-Conde, Susana (Committee member) / Macknik, Stephen L. (Committee member) / Baer, Stephen (Committee member) / McCamy, Michael B (Committee member) / Arizona State University (Publisher)
Created2014
Description
Dopamine (DA) is a neurotransmitter involved in attention, goal oriented behavior, movement, reward learning, and short term and working memory. For the past four decades, mathematical and computational modeling approaches have been useful in DA research, and although every modeling approach has limitations, a model is an efficient way to generate and explore hypotheses. This work develops a model of DA dynamics in a representative, single DA neuron by integrating previous experimental, theoretical and computational research. The model consists of three compartments: the cytosol, the vesicles, and the extracellular space and forms the basis of a new mathematical paradigm for examining the dynamics of DA synthesis, storage, release and reuptake. The model can be driven by action potentials generated by any model of excitable membrane potential or even from experimentally induced depolarization voltage recordings. Here the model is forced by a previously published model of the excitable membrane of a mesencephalic DA neuron in order to study the biochemical processes involved in extracellular DA production. After demonstrating that the model exhibits realistic dynamics resembling those observed experimentally, the model is used to examine the functional changes in presynaptic mechanisms due to application of cocaine. Sensitivity analysis and numerical studies that focus on various possible mechanisms for the inhibition of DAT by cocaine provide insight for the complex interactions involved in DA dynamics. In particular, comparing numerical results for a mixed inhibition mechanism to those for competitive, non-competitive and uncompetitive inhibition mechanisms reveals many behavioral similarities for these different types of inhibition that depend on inhibition parameters and levels of cocaine. Placing experimental results within this context of mixed inhibition provides a possible explanation for the conflicting views of uptake inhibition mechanisms found in experimental neuroscience literature.
ContributorsTello-Bravo, David (Author) / Crook, Sharon M (Thesis advisor) / Greenwood, Priscilla E (Thesis advisor) / Baer, Steven M. (Committee member) / Castaneda, Edward (Committee member) / Castillo-Chavez, Carlos (Committee member) / Arizona State University (Publisher)
Created2012
Description
The RAS/MAPK (RAS/Mitogen Activated Protein Kinase) pathway is a highly conserved, canonical signaling cascade that is highly involved in cellular growth and proliferation as well as cell migration. As such, it plays an important role in development, specifically in development of the nervous system. Activation of ERK is indispensable for the differentiation of Embryonic Stem Cells (ESC) into neuronal precursors (Li z et al, 2006). ERK signaling has also shown to mediate Schwann cell myelination of the peripheral nervous system (PNS) as well as oligodendrocyte proliferation (Newbern et al, 2011). The class of developmental disorders that result in the dysregulation of RAS signaling are known as RASopathies. The molecular and cell-specific consequences of these various pathway mutations remain to be elucidated. While there is evidence for altered DNA transcription in RASopathies, there is little work examining the effects of the RASopathy-linked mutations on protein translation and post-translational modifications in vivo. RASopathies have phenotypic and molecular similarities to other disorders such as Fragile X Syndrome (FXS) and Tuberous Sclerosis (TSC) that show evidence of aberrant protein synthesis and affect related pathways. There are also well-defined downstream RAS pathway elements involved in translation. Additionally, aberrant corticospinal axon outgrowth has been observed in disease models of RASopathies (Xing et al, 2016). For these reasons, this present study examines a subset of proteins involved in translation and translational regulation in the context of RASopathy disease states. Results indicate that in both of the tested RASopathy model systems, there is altered mTOR expression. Additionally the loss of function model showed a decrease in rps6 activation. This data supports a role for the selective dysregulation of translational control elements in RASopathy models. This data also indicates that the primary candidate mechanism for control of altered translation in these modes is through the altered expression of mTOR.
ContributorsHilbert, Alexander Robert (Author) / Newbern, Jason (Thesis director) / Olive, M. Foster (Committee member) / Bjorklund, Reed (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Evidence from the 20th century demonstrated that early life stress (ELS) produces long lasting neuroendocrine and behavioral effects related to an increased vulnerability towards psychiatric illnesses such as major depressive disorder, post-traumatic stress disorder, schizophrenia, and substance use disorder. Substance use disorders (SUDs) are complex neurological and behavioral psychiatric illnesses. The development, maintenance, and relapse of SUDs involve multiple brain systems and are affected by many variables, including socio-economic and genetic factors. Pre-clinical studies demonstrate that ELS affects many of the same systems, such as the reward circuitry and executive function involved with addiction-like behaviors. Previous research has focused on cocaine, ethanol, opiates, and amphetamine, while few studies have investigated ELS and methamphetamine (METH) vulnerability. METH is a highly addictive psychostimulant that when abused, has deleterious effects on the user and society. However, a critical unanswered question remains; how do early life experiences modulate both neural systems and behavior in adulthood? The emerging field of neuroepigenetics provides a potential answer to this question. Methyl CpG binding protein 2 (MeCP2), an epigenetic tag, has emerged as one possible mediator between initial drug use and the transition to addiction. Additionally, there are various neural systems that undergo long lasting epigenetics changes after ELS, such as the response of the hypothalamo-pituitary-adrenal (HPA) axis to stressors. Despite this, little attention has been given to the interactions between ELS, epigenetics, and addiction vulnerability. The studies described herein investigated the effects of ELS on METH self-administration (SA) in adult male rats. Next, we investigated the effects of ELS and METH SA on MeCP2 expression in the nucleus accumbens and dorsal striatum. Additionally, we investigated the effects of virally-mediated knockdown of MeCP2 expression in the nucleus accumbens core on METH SA, motivation to obtain METH under conditions of increasing behavioral demand, and reinstatement of METH-seeking in rats with and without a history of ELS. The results of these studies provide insights into potential epigenetic mechanisms by which ELS can produce an increased vulnerability to addiction in adulthood. Moreover, these studies shed light on possible novel molecular targets for treating addiction in individuals with a history of ELS.
ContributorsLewis, Candace (Author) / Olive, M. Foster (Thesis advisor) / Hammer, Ronald (Committee member) / Neisewander, Janet (Committee member) / Sanabria, Federico (Committee member) / Arizona State University (Publisher)
Created2015
Description
Electrical stimulation of the human peripheral nervous system can be a powerful tool to treat various medical conditions and provide insight into nervous system processes. A critical challenge for many applications is to selectively activate neurons that have the desired effect while avoiding the activation of neurons that produce side effects. To stimulate peripheral fibers, the longitudinal intrafascicular electrode (LIFE) targets small groups of fibers inside the fascicle using low-amplitude pulses and is well-suited for chronic use. This work aims to understand better the ability to use intrafascicular stimulation with LIFEs to activate small groups of neurons within a fascicle selectively.A hybrid workflow was developed to simulate: 1) the production/propagation of the electric field induced by the stimulation pulse and 2) the effect of the electric field on fiber activation (recruitment). To create efficient and robust strategies for the selective recruitment of axons, recognizing the effect of each parameter on their recruitment and activation pattern is essential. Thus, using this hybrid workflow, the effects of various factors such as fascicular anatomy, electrode parameters, and stimulation pulse parameters on recruitment have been characterized, and the sensitivity of the recruitment patterns to these parameters has been explored.
Results demonstrated the potential advantages of specific stimulation strategies and the sensitivity of recruitment patterns to electrode placement and tissue properties. For example, it is demonstrated: the significant effect of endoneurium conductivities on threshold levels; that a configuration with a LIFE as a local ground can be used to deselect its surrounding axons; the advantages of changing the delay between pulses in dual monopolar stimulation in targeting different axons clusters and increasing the activation frequency of some axons; how monopolar and bipolar configurations can be used to enhance spatial selectivity; the effect of longitudinal displacement of axons, electrode length and electrode movement on the recruitment and the activation pattern. In summary, this work forms the foundation for developing stimulation strategies to enhance the selectivity that can be achieved with intrafascicular stimulation.
ContributorsRouhani, Morteza (Author) / Abbas, James J (Thesis advisor) / Crook, Sharon M (Thesis advisor) / Baer, Steven M (Committee member) / Sadleir, Rosalind (Committee member) / Gardner, Carl (Committee member) / Arizona State University (Publisher)
Created2022
Description
The increasing availability of experimental data and computational power have resulted in increasingly detailed and sophisticated models of brain structures. Biophysically realistic models allow detailed investigations of the mechanisms that operate within those structures. In this work, published mouse experimental data were synthesized to develop an extensible, open-source platform for modeling the mouse main olfactory bulb and other brain regions. A “virtual slice” model of a main olfactory bulb glomerular column that includes detailed models of tufted, mitral, and granule cells was created to investigate the underlying mechanisms of a gamma frequency oscillation pattern (“gamma fingerprint”) often observed in rodent bulbar local field potential recordings. The gamma fingerprint was reproduced by the model and a mechanistic hypothesis to explain aspects of the fingerprint was developed. A series of computational experiments tested the hypothesis. The results demonstrate the importance of interactions between electrical synapses, principal cell synaptic input strength differences, and granule cell inhibition in the formation of the gamma fingerprint. The model, data, results, and reproduction materials are accessible at https://github.com/justasb/olfactorybulb. The discussion includes a detailed description of mechanisms underlying the gamma fingerprint and how the model predictions can be tested experimentally. In summary, the modeling platform can be extended to include other types of cells, mechanisms and brain regions and can be used to investigate a wide range of experimentally testable hypotheses.
ContributorsBirgiolas, Justas (Author) / Crook, Sharon M (Thesis advisor) / Gerkin, Richard C (Committee member) / Smith, Brian H. (Committee member) / Neisewander, Janet (Committee member) / Calhoun, Ronald (Committee member) / Arizona State University (Publisher)
Created2019
Description
Neuron models that behave like their biological counterparts are essential for computational neuroscience.Reduced neuron models, which abstract away biological mechanisms in the interest of speed and interpretability, have received much attention due to their utility in large scale simulations of the brain, but little care has been taken to ensure that these models exhibit behaviors that closely resemble real neurons.
In order to improve the verisimilitude of these reduced neuron models, I developed an optimizer that uses genetic algorithms to align model behaviors with those observed in experiments.
I verified that this optimizer was able to recover model parameters given only observed physiological data; however, I also found that reduced models nonetheless had limited ability to reproduce all observed behaviors, and that this varied by cell type and desired behavior.
These challenges can partly be surmounted by carefully designing the set of physiological features that guide the optimization. In summary, we found evidence that reduced neuron model optimization had the potential to produce reduced neuron models for only a limited range of neuron types.
In order to improve the verisimilitude of these reduced neuron models, I developed an optimizer that uses genetic algorithms to align model behaviors with those observed in experiments.
I verified that this optimizer was able to recover model parameters given only observed physiological data; however, I also found that reduced models nonetheless had limited ability to reproduce all observed behaviors, and that this varied by cell type and desired behavior.
These challenges can partly be surmounted by carefully designing the set of physiological features that guide the optimization. In summary, we found evidence that reduced neuron model optimization had the potential to produce reduced neuron models for only a limited range of neuron types.
ContributorsJarvis, Russell Jarrod (Author) / Crook, Sharon M (Thesis advisor) / Gerkin, Richard C (Thesis advisor) / Zhou, Yi (Committee member) / Abbas, James J (Committee member) / Arizona State University (Publisher)
Created2020
Description
It is increasingly common to see machine learning techniques applied in conjunction with computational modeling for data-driven research in neuroscience. Such applications include using machine learning for model development, particularly for optimization of parameters based on electrophysiological constraints. Alternatively, machine learning can be used to validate and enhance techniques for experimental data analysis or to analyze model simulation data in large-scale modeling studies, which is the approach I apply here. I use simulations of biophysically-realistic cortical neuron models to supplement a common feature-based technique for analysis of electrophysiological signals. I leverage these simulated electrophysiological signals to perform feature selection that provides an improved method for neuron-type classification. Additionally, I validate an unsupervised approach that extends this improved feature selection to discover signatures associated with neuron morphologies - performing in vivo histology in effect. The result is a simulation-based discovery of the underlying synaptic conditions responsible for patterns of extracellular signatures that can be applied to understand both simulation and experimental data. I also use unsupervised learning techniques to identify common channel mechanisms underlying electrophysiological behaviors of cortical neuron models. This work relies on an open-source database containing a large number of computational models for cortical neurons. I perform a quantitative data-driven analysis of these previously published ion channel and neuron models that uses information shared across models as opposed to information limited to individual models. The result is simulation-based discovery of model sub-types at two spatial scales which map functional relationships between activation/inactivation properties of channel family model sub-types to electrophysiological properties of cortical neuron model sub-types. Further, the combination of unsupervised learning techniques and parameter visualizations serve to integrate characterizations of model electrophysiological behavior across scales.
ContributorsHaynes, Reuben (Author) / Crook, Sharon M (Thesis advisor) / Gerkin, Richard C (Committee member) / Zhou, Yi (Committee member) / Baer, Steven (Committee member) / Armbruster, Hans D (Committee member) / Arizona State University (Publisher)
Created2020